Kovach Christopher K, Gander Phillip E
Department of Neurosurgery, The University of Iowa College of Medicine, United States.
Department of Neurosurgery, The University of Iowa College of Medicine, United States.
J Neurosci Methods. 2016 Mar 1;261:135-54. doi: 10.1016/j.jneumeth.2015.12.004. Epub 2015 Dec 19.
Windowed Fourier decompositions (WFD) are widely used in measuring stationary and non-stationary spectral phenomena and in describing pairwise relationships among multiple signals. Although a variety of WFDs see frequent application in electrophysiological research, including the short-time Fourier transform, continuous wavelets, bandpass filtering and multitaper-based approaches, each carries certain drawbacks related to computational efficiency and spectral leakage. This work surveys the advantages of a WFD not previously applied in electrophysiological settings.
A computationally efficient form of complex demodulation, the demodulated band transform (DBT), is described.
DBT is shown to provide an efficient approach to spectral estimation with minimal susceptibility to spectral leakage. In addition, it lends itself well to adaptive filtering of non-stationary narrowband noise.
A detailed comparison with alternative WFDs is offered, with an emphasis on the relationship between DBT and Thomson's multitaper. DBT is shown to perform favorably in combining computational efficiency with minimal introduction of spectral leakage.
DBT is ideally suited to efficient estimation of both stationary and non-stationary spectral and cross-spectral statistics with minimal susceptibility to spectral leakage. These qualities are broadly desirable in many settings.
加窗傅里叶分解(WFD)广泛应用于测量平稳和非平稳频谱现象以及描述多个信号之间的成对关系。尽管多种WFD在电生理研究中经常应用,包括短时傅里叶变换、连续小波变换、带通滤波和基于多窗谱分析的方法,但每种方法都存在与计算效率和频谱泄漏相关的某些缺点。本研究探讨了一种此前未应用于电生理环境的WFD的优点。
描述了一种计算效率高的复解调形式,即解调带通变换(DBT)。
DBT被证明是一种有效的频谱估计方法,对频谱泄漏的敏感性最小。此外,它非常适合对非平稳窄带噪声进行自适应滤波。
对替代WFD进行了详细比较,重点是DBT与汤姆森多窗谱分析之间的关系。结果表明,DBT在结合计算效率和最小化频谱泄漏方面表现良好。
DBT非常适合高效估计平稳和非平稳频谱及互谱统计量,对频谱泄漏的敏感性最小。这些特性在许多情况下都非常有用。